Organization
of charts and
applications
of OES data
The presentation of figures in this
chartbook is intended to demonstrate a
variety of applications of OES
data. Figures are organized into
five sections: the first focuses on
a general overview of OES data,
the others highlight occupational,
geographic, and industry topics in jobs
related to construction, healthcare,
manufacturing, and STEM (science,
technology, engineering, and
mathematics). The following are
some examples of useful applications of
OES data:
Detailed occupational data can be used by jobseekers
or employers to study wages for workers in certain
occupations and to assess wage variation within and
across occupations. Wage variation within an occupation
can result from several factors, including industry,
geographic location, or a worker’s individual experience
or qualifications. Useful data for jobseekers include
information on the industries or geographic areas that have
the highest employment or the highest average wages
for an occupation. Career and guidance counselors can
use OES data to examine information on the possible
occupational choices of their clients.
Industry-specific occupational data can be used by human
resources professionals in salary negotiations or to ensure
that their wages are competitive with those of other
businesses in their area or industry. Information on the
types of jobs within an industry can be used to compare
average staffing patterns with the staffing pattern of one’s
own company. Occupational employment by industry may
be useful in assessing the impact of shifts in technology and
other macroeconomic trends on the types of jobs available.
BLS and state government employment projections
programs use OES data as an input to their employment
projections, which can be used to predict training and
education demands.
Information about geographic areas can be used to assess
labor market features of a particular area. OES state-level
x
data can be used to make assessments about the diversity of
a state’s economy or to make comparisons among
states. The occupational composition of employment can
provide clues to how a state or regional economy can hold
up in adverse conditions that affect a certain sector of the
economy. Differences in both occupational composition
and occupational wage rates also help explain differences
in average wages across states. For example, states with
high average wages may have larger employment shares
of high-paying occupations, higher wages within each
occupation, or some combination of both factors.
Like state data, metropolitan and nonmetropolitan area data
can be used to study the diversity of local area economies.
Businesses can use data to see whether it might be
beneficial to relocate to a particular area. OES wage data
can be used to compare wages across alternative areas as
part of an analysis of labor costs. OES occupational
employment data may indicate whether workers are
available in occupations that the business will need. For
example, businesses that require computer specialists or
skilled production workers may want to identify areas that
have high employment in these occupations.